Internet of Things (IoT) is an emerging disruptive technology and becoming an increasing topic of interest. One of the areas of IoT application is the connected vehicles. In this article we'll use Apache Spark and Kafka technologies to analyse and process IoT connected vehicle's data and send the processed data to real time traffic monitoring dashboard.
With support for Machine Learning data pipelines, Apache Spark framework is a great choice for building a unified use case that combines ETL, batch analytics, streaming data analysis, and machine learning. In this fifth installment of Apache Spark article series, author Srini Penchikala discusses Spark ML package and how to use it to create and manage machine learning data pipelines.
"Site Reliability Engineering - How Google Runs Production Systems" is an open window into Google's experience and expertise on running some of the largest IT systems in the world. The book describes the principles that underpin the Site Reliability Engineering discipline. It also details the key practices that allow Google to grow at breakneck speed without sacrificing performance or reliability.
InfoQ spoke with authors of Spark GraphX in Action book, Apache Spark framework and what's coming up in the area of graph data processing and analytics.
InfoQ interviews Chris Fregly, organizer for the 4000+ member Advanced Spark and TensorFlow Meetup about the PANCAKE STACK workshop, Spark and building data pipelines for a machine learning pipeline
Christine Doig spoke at OSCON Conference about data science as a team discipline and how to navigate data science Python ecosystem. InfoQ spoke with Christine about challenges of data science teams.
We review the book Infrastructure as Code by Kief Morris, who lays down the foundation for Infrastructure as Code and outlines the main patterns and practices recommended for building it.
Big Data Analytics with Spark, authored by Mohammed Guller, provides a practical guide for learning Apache Spark. InfoQ and the author discuss the book & development tools for big data applications.
In this fourth installment of Apache Spark article series, author Srini Penchikala discusses machine learning concept & Spark MLlib library for running predictive analytics using a sample application.
Olivier Bonsignour on what "X-Raying" software means, how it can help prevent software disasters and why CIOs should care. 3
Data Science has been getting lot of attention as organizations are starting to use data analytics to gain insights into their data. This article takes a closer look at Data Scientist role in 2016.
Current enterprise data architectures include NoSQL databases co-existing with RDBMS. In this article, author discusses a solution for managing NoSQL & relational data using unified data modeling. 5